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Here is the more relevant paper released by OpenAI. [1] It obsesses on dangers, misuse, and abuse for a model which was mostly incoherent. [1] - https://arxiv.

Here is the more relevant paper released by OpenAI. [1] It obsesses on dangers, misuse, and abuse for a model which was mostly incoherent. [1] - https://arxiv.org/pdf/1908.09203 https://arxiv.org/pdf/1908.09203

ben_w 2y ago
Given that "being 100% right" isn't possible because they're not omniscient, would you rather they embarrass themselves by being a little too cautious and saying "let's experiment" and "here's what we found from our experiment" 1.5 versions before it turned out to matter, or would you instead prefer they had let everyone download 3.5 without any restrictions because they hadn't even stopped to think about what might possibly go wrong? (Failing to stop and think in advance what might go wrong, seems to be why Facebook didn't invest much in moderating the content in Burma until much too late; they'd have also looked to many people like they were 'worrying about nothing' if they'd done that investing before the genocide gave everyone a concrete example of why that matters) All of the stuff I saw OpenAI being concerned about in the link, has in fact happened with the bigger models (that said, this is a skim-reading, not an exhaustive analysis): -- """We chose a staged release process, releasing the smallest model in February, but withholding larger models due to concerns about the potential for misuse, such as generating fake news content, impersonating others in email, or au- tomating abusive social media content production [56].""" (Basically all of that) """One key variable affecting the social impact of language models is the extent to which humans and machines can detect outputs. We found reasons for optimism as well as reasons to continue being vigilant about the misuse of language models going forward. Our thoughts on detection at this time are: • Humans can be deceived by text generated by GPT-2 and other successful language models, and human detectability will likely become increasingly more difficult.""" (I've been accused, here, of being an LLM. Have you, yet?) """Security: There is a tradeoff between the number of partners and the likelihood of a model being prematurely released, accounting for hacks and leaks. Fairness: The high cost of compute used in powerful models like GPT-2 raises concerns about accessibility and equity in future AI research [13]. Private model sharing should not excessively harm researchers with limited computing resources, and conflicts of interest related to model sharing should be avoided in commercial contexts.""" (One of the GPT-2 models got leaked, so did one of the LLaMA models; at the same time, there's loads of people who think it's big and clever to call OpenAI "ClosedAI" and even to throw hissy fits about the other models failing to provide the training set and thus revealing that they have no idea how expensive the models are to train).
- somenameforme 2y ago
  The claim is that they were being hyperbolic in an effort to generate hype for their product. You claimed 'people have bad memories' and they never made such claims. Now you are stating 'okay they made such claims, but...' So far as I can tell of your opinion - if they made such claims OpenAI wins, if they didn't make such claims OpenAI wins. Gee, I wonder what your opinion is.
  - ben_w 2y ago
    None of the claims in the paper are hyperbolic, they happened. An experiment to find something out isn't hyperbolic even when the result is "hahah no". A requirement for the concept of a test is more than one possible answer. Paying attention to potential risks before you have had a chance to evaluate them, is exactly what people demand whenever a group fails to do so and finds out there was a risk by causing harm. Or have you never noticed that? "Why didn't the government prevent this attack!" and "Why didn't Facebook realise their software was enabling a genocide!" etc. Perhaps I was being overly generous by blaming this on memory rather than on reading worse than the very LLM being laughed at.

ben_w 2y ago

Given that "being 100% right" isn't possible because they're not omniscient, would you rather they embarrass themselves by being a little too cautious and saying "let's experiment" and "here's what we found from our experiment" 1.5 versions before it turned out to matter, or would you instead prefer they had let everyone download 3.5 without any restrictions because they hadn't even stopped to think about what might possibly go wrong? (Failing to stop and think in advance what might go wrong, seems to be why Facebook didn't invest much in moderating the content in Burma until much too late; they'd have also looked to many people like they were 'worrying about nothing' if they'd done that investing before the genocide gave everyone a concrete example of why that matters) All of the stuff I saw OpenAI being concerned about in the link, has in fact happened with the bigger models (that said, this is a skim-reading, not an exhaustive analysis): -- """We chose a staged release process, releasing the smallest model in February, but withholding larger models due to concerns about the potential for misuse, such as generating fake news content, impersonating others in email, or au- tomating abusive social media content production [56].""" (Basically all of that) """One key variable affecting the social impact of language models is the extent to which humans and machines can detect outputs. We found reasons for optimism as well as reasons to continue being vigilant about the misuse of language models going forward. Our thoughts on detection at this time are: • Humans can be deceived by text generated by GPT-2 and other successful language models, and human detectability will likely become increasingly more difficult.""" (I've been accused, here, of being an LLM. Have you, yet?) """Security: There is a tradeoff between the number of partners and the likelihood of a model being prematurely released, accounting for hacks and leaks. Fairness: The high cost of compute used in powerful models like GPT-2 raises concerns about accessibility and equity in future AI research [13]. Private model sharing should not excessively harm researchers with limited computing resources, and conflicts of interest related to model sharing should be avoided in commercial contexts.""" (One of the GPT-2 models got leaked, so did one of the LLaMA models; at the same time, there's loads of people who think it's big and clever to call OpenAI "ClosedAI" and even to throw hissy fits about the other models failing to provide the training set and thus revealing that they have no idea how expensive the models are to train).

somenameforme 2y ago
The claim is that they were being hyperbolic in an effort to generate hype for their product. You claimed 'people have bad memories' and they never made such claims. Now you are stating 'okay they made such claims, but...' So far as I can tell of your opinion - if they made such claims OpenAI wins, if they didn't make such claims OpenAI wins. Gee, I wonder what your opinion is.
- ben_w 2y ago
  None of the claims in the paper are hyperbolic, they happened. An experiment to find something out isn't hyperbolic even when the result is "hahah no". A requirement for the concept of a test is more than one possible answer. Paying attention to potential risks before you have had a chance to evaluate them, is exactly what people demand whenever a group fails to do so and finds out there was a risk by causing harm. Or have you never noticed that? "Why didn't the government prevent this attack!" and "Why didn't Facebook realise their software was enabling a genocide!" etc. Perhaps I was being overly generous by blaming this on memory rather than on reading worse than the very LLM being laughed at.